prac4_rmarkdown

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(raster)

## Loading required package: sp

## 
## Attaching package: 'raster'

## The following object is masked from 'package:plotly':
## 
##     select

library(weathermetrics)
library(tidyverse)

## ── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──

## ✓ tibble  3.0.3     ✓ dplyr   1.0.2
## ✓ tidyr   1.1.2     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.0
## ✓ purrr   0.3.4

## ── Conflicts ────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## x tidyr::extract() masks raster::extract()
## x dplyr::filter()  masks plotly::filter(), stats::filter()
## x dplyr::lag()     masks stats::lag()
## x dplyr::select()  masks raster::select(), plotly::select()

GB_auto <- raster::getData('GADM', 
                           country="GBR", 
                           level=0, 
                           #set the path to store your data in
                           path='prac4_data/', 
                           download=TRUE)

GBclim <- raster::getData("worldclim", 
                          res=5, 
                          var="tmean",
                          #set the path to store your data in
                          path='prac4_data/', 
                          download=TRUE)

month <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", 
           "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")
names(GBclim) <- month

GBtemp <- GBclim %>%
  crop(., GB_auto)%>%
  #WorldClim data has a scale factor of 10!
  mask(., GB_auto)/10

alldf <- GBtemp %>% 
  as.data.frame()%>%
  pivot_longer(
  cols = 1:12,
  names_to = "Month",
  values_to = "Temp")%>%
  drop_na()

jan<-filter(alldf, Month=="Jan")
jun<-filter(alldf, Month=="Jun")

# give axis titles
x <- list (title = "Temperature")
y <- list (title = "Frequency")

# set the bin width
xbinsno<-list(start=-5, end=20, size = 2.5)

# plot the histogram calling all the variables we just set
ihist<-plot_ly(alpha = 0.6) %>%
        add_histogram(x = jan$Temp,
        xbins=xbinsno, name="January") %>%
        add_histogram(x = jun$Temp,
        xbins=xbinsno, name="June") %>% 
        layout(barmode = "overlay", xaxis=x, yaxis=y)

ihist

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)

##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.